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<h1 id="index">Index</h1>

<div class="genindex-jumpbox">
 <a href="#_"><strong>_</strong></a>
 | <a href="#A"><strong>A</strong></a>
 | <a href="#B"><strong>B</strong></a>
 | <a href="#C"><strong>C</strong></a>
 | <a href="#D"><strong>D</strong></a>
 | <a href="#E"><strong>E</strong></a>
 | <a href="#F"><strong>F</strong></a>
 | <a href="#G"><strong>G</strong></a>
 | <a href="#H"><strong>H</strong></a>
 | <a href="#I"><strong>I</strong></a>
 | <a href="#L"><strong>L</strong></a>
 | <a href="#M"><strong>M</strong></a>
 | <a href="#N"><strong>N</strong></a>
 | <a href="#O"><strong>O</strong></a>
 | <a href="#P"><strong>P</strong></a>
 | <a href="#R"><strong>R</strong></a>
 | <a href="#S"><strong>S</strong></a>
 | <a href="#T"><strong>T</strong></a>
 | <a href="#U"><strong>U</strong></a>
 | <a href="#V"><strong>V</strong></a>
 
</div>
<h2 id="_">_</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.input_layer.html#ultra.input_layer.base_input_feed.BaseInputFeed.__init__">__init__() (ultra.input_layer.base_input_feed.BaseInputFeed method)</a>

      <ul>
        <li><a href="ultra.input_layer.html#ultra.input_layer.click_simulation_feed.ClickSimulationFeed.__init__">(ultra.input_layer.click_simulation_feed.ClickSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed.__init__">(ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.direct_label_feed.DirectLabelFeed.__init__">(ultra.input_layer.direct_label_feed.DirectLabelFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed.__init__">(ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed.__init__">(ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.base_algorithm.BaseAlgorithm.__init__">(ultra.learning_algorithm.base_algorithm.BaseAlgorithm method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dbgd.DBGD.__init__">(ultra.learning_algorithm.dbgd.DBGD method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.DLA.__init__">(ultra.learning_algorithm.dla.DLA method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.ipw_rank.IPWrank.__init__">(ultra.learning_algorithm.ipw_rank.IPWrank method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.navie_algorithm.NavieAlgorithm.__init__">(ultra.learning_algorithm.navie_algorithm.NavieAlgorithm method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.pairwise_debias.PairDebias.__init__">(ultra.learning_algorithm.pairwise_debias.PairDebias method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.pdgd.PDGD.__init__">(ultra.learning_algorithm.pdgd.PDGD method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.regression_EM.RegressionEM.__init__">(ultra.learning_algorithm.regression_EM.RegressionEM method)</a>
</li>
        <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.BaseRankingModel.__init__">(ultra.ranking_model.base_ranking_model.BaseRankingModel method)</a>
</li>
        <li><a href="ultra.utils.html#ultra.utils.data_utils.Raw_data.__init__">(ultra.utils.data_utils.Raw_data method)</a>
</li>
        <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.__init__">(ultra.utils.hparams.HParams method)</a>
</li>
        <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.BasicPropensityEstimator.__init__">(ultra.utils.propensity_estimator.BasicPropensityEstimator method)</a>
</li>
        <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.OraclePropensityEstimator.__init__">(ultra.utils.propensity_estimator.OraclePropensityEstimator method)</a>
</li>
        <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.RandomizedPropensityEstimator.__init__">(ultra.utils.propensity_estimator.RandomizedPropensityEstimator method)</a>
</li>
        <li><a href="ultra.utils.html#ultra.utils.team_draft_interleave.TeamDraftInterleaving.__init__">(ultra.utils.team_draft_interleave.TeamDraftInterleaving method)</a>
</li>
      </ul></li>
  </ul></td>
</tr></table>

<h2 id="A">A</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.BaseRankingModel.ACT_FUNC_DIC">ACT_FUNC_DIC (ultra.ranking_model.base_ranking_model.BaseRankingModel attribute)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.ActivationFunctions">ActivationFunctions (class in ultra.ranking_model.base_ranking_model)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.add_hparam">add_hparam() (ultra.utils.hparams.HParams method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.RankingMetricKey.ARP">ARP (ultra.utils.metrics.RankingMetricKey attribute)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.average_relevance_position">average_relevance_position() (in module ultra.utils.metrics)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="B">B</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.base_algorithm.BaseAlgorithm">BaseAlgorithm (class in ultra.learning_algorithm.base_algorithm)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.base_input_feed.BaseInputFeed">BaseInputFeed (class in ultra.input_layer.base_input_feed)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.BaseRankingModel">BaseRankingModel (class in ultra.ranking_model.base_ranking_model)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.BasicPropensityEstimator">BasicPropensityEstimator (class in ultra.utils.propensity_estimator)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.NormalizationFunctions.BATCH">BATCH (ultra.ranking_model.base_ranking_model.NormalizationFunctions attribute)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.BaseRankingModel.build">build() (ultra.ranking_model.base_ranking_model.BaseRankingModel method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="C">C</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.DLA.click_weighted_log_loss">click_weighted_log_loss() (ultra.learning_algorithm.dla.DLA method)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.DLA.click_weighted_pairwise_loss">click_weighted_pairwise_loss() (ultra.learning_algorithm.dla.DLA method)</a>

      <ul>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.ipw_rank.IPWrank.click_weighted_pairwise_loss">(ultra.learning_algorithm.ipw_rank.IPWrank method)</a>
</li>
      </ul></li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.DLA.click_weighted_softmax_cross_entropy_loss">click_weighted_softmax_cross_entropy_loss() (ultra.learning_algorithm.dla.DLA method)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.ipw_rank.IPWrank.click_weighted_softmax_loss">click_weighted_softmax_loss() (ultra.learning_algorithm.ipw_rank.IPWrank method)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.click_simulation_feed.ClickSimulationFeed">ClickSimulationFeed (class in ultra.input_layer.click_simulation_feed)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.Initializer.CONSTANT">CONSTANT (ultra.ranking_model.base_ranking_model.Initializer attribute)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.sys_tools.create_object">create_object() (in module ultra.utils.sys_tools)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="D">D</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dbgd.DBGD">DBGD (class in ultra.learning_algorithm.dbgd)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.RankingMetricKey.DCG">DCG (ultra.utils.metrics.RankingMetricKey attribute)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.DLA.DenoisingNet">DenoisingNet() (ultra.learning_algorithm.dla.DLA method)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.input_layer.html#ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed">DeterministicOnlineSimulationFeed (class in ultra.input_layer.deterministic_online_simulation_feed)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.direct_label_feed.DirectLabelFeed">DirectLabelFeed (class in ultra.input_layer.direct_label_feed)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.discounted_cumulative_gain">discounted_cumulative_gain() (in module ultra.utils.metrics)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.DLA">DLA (class in ultra.learning_algorithm.dla)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="E">E</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.ActivationFunctions.ELU">ELU (ultra.ranking_model.base_ranking_model.ActivationFunctions attribute)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.RankingMetricKey.ERR">ERR (ultra.utils.metrics.RankingMetricKey attribute)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.RandomizedPropensityEstimator.estimateParametersFromModel">estimateParametersFromModel() (ultra.utils.propensity_estimator.RandomizedPropensityEstimator method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.expected_reciprocal_rank">expected_reciprocal_rank() (in module ultra.utils.metrics)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="F">F</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.sys_tools.find_class">find_class() (in module ultra.utils.sys_tools)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.from_proto">from_proto() (ultra.utils.hparams.HParams static method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="G">G</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.generate_ranklist">generate_ranklist() (in module ultra.utils.data_utils)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.generate_ranklist_by_scores">generate_ranklist_by_scores() (in module ultra.utils.data_utils)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.get">get() (ultra.utils.hparams.HParams method)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.base_input_feed.BaseInputFeed.get_batch">get_batch() (ultra.input_layer.base_input_feed.BaseInputFeed method)</a>

      <ul>
        <li><a href="ultra.input_layer.html#ultra.input_layer.click_simulation_feed.ClickSimulationFeed.get_batch">(ultra.input_layer.click_simulation_feed.ClickSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed.get_batch">(ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.direct_label_feed.DirectLabelFeed.get_batch">(ultra.input_layer.direct_label_feed.DirectLabelFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed.get_batch">(ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed.get_batch">(ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed method)</a>
</li>
      </ul></li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.pairwise_debias.get_bernoulli_sample">get_bernoulli_sample() (in module ultra.learning_algorithm.pairwise_debias)</a>

      <ul>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.regression_EM.get_bernoulli_sample">(in module ultra.learning_algorithm.regression_EM)</a>
</li>
      </ul></li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.base_input_feed.BaseInputFeed.get_data_by_index">get_data_by_index() (ultra.input_layer.base_input_feed.BaseInputFeed method)</a>

      <ul>
        <li><a href="ultra.input_layer.html#ultra.input_layer.click_simulation_feed.ClickSimulationFeed.get_data_by_index">(ultra.input_layer.click_simulation_feed.ClickSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed.get_data_by_index">(ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.direct_label_feed.DirectLabelFeed.get_data_by_index">(ultra.input_layer.direct_label_feed.DirectLabelFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed.get_data_by_index">(ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed.get_data_by_index">(ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.get_model_structure">get_model_structure() (ultra.utils.hparams.HParams method)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.base_input_feed.BaseInputFeed.get_next_batch">get_next_batch() (ultra.input_layer.base_input_feed.BaseInputFeed method)</a>

      <ul>
        <li><a href="ultra.input_layer.html#ultra.input_layer.click_simulation_feed.ClickSimulationFeed.get_next_batch">(ultra.input_layer.click_simulation_feed.ClickSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed.get_next_batch">(ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.direct_label_feed.DirectLabelFeed.get_next_batch">(ultra.input_layer.direct_label_feed.DirectLabelFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed.get_next_batch">(ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed.get_next_batch">(ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed method)</a>
</li>
      </ul></li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.DLA.get_normalized_weights">get_normalized_weights() (ultra.learning_algorithm.dla.DLA method)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.base_algorithm.BaseAlgorithm.get_ranking_scores">get_ranking_scores() (ultra.learning_algorithm.base_algorithm.BaseAlgorithm method)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.BaseRankingModel.get_variable">get_variable() (ultra.ranking_model.base_ranking_model.BaseRankingModel method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.BasicPropensityEstimator.getPropensityForOneList">getPropensityForOneList() (ultra.utils.propensity_estimator.BasicPropensityEstimator method)</a>

      <ul>
        <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.OraclePropensityEstimator.getPropensityForOneList">(ultra.utils.propensity_estimator.OraclePropensityEstimator method)</a>
</li>
      </ul></li>
  </ul></td>
</tr></table>

<h2 id="H">H</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams">HParams (class in ultra.utils.hparams)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="I">I</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.team_draft_interleave.TeamDraftInterleaving.infer_winner">infer_winner() (ultra.utils.team_draft_interleave.TeamDraftInterleaving method)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.Initializer">Initializer (class in ultra.ranking_model.base_ranking_model)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.BaseRankingModel.INITIALIZER_DIC">INITIALIZER_DIC (ultra.ranking_model.base_ranking_model.BaseRankingModel attribute)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.team_draft_interleave.TeamDraftInterleaving.interleave">interleave() (ultra.utils.team_draft_interleave.TeamDraftInterleaving method)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed">InterleavingDeterministicOnlineSimulationFeed (class in ultra.input_layer.interleaving_deterministic_online_simulation_feed)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.ipw_rank.IPWrank">IPWrank (class in ultra.learning_algorithm.ipw_rank)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="L">L</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.NormalizationFunctions.LAYER">LAYER (ultra.ranking_model.base_ranking_model.NormalizationFunctions attribute)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.list_available">list_available() (in module ultra.input_layer)</a>

      <ul>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.list_available">(in module ultra.learning_algorithm)</a>
</li>
        <li><a href="ultra.ranking_model.html#ultra.ranking_model.list_available">(in module ultra.ranking_model)</a>
</li>
      </ul></li>
      <li><a href="ultra.utils.html#ultra.utils.sys_tools.list_recursive_concrete_subclasses">list_recursive_concrete_subclasses() (in module ultra.utils.sys_tools)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.Raw_data.load_basic_data_information">load_basic_data_information() (ultra.utils.data_utils.Raw_data method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.Raw_data.load_data_in_libsvm_format">load_data_in_libsvm_format() (ultra.utils.data_utils.Raw_data method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.Raw_data.load_data_in_ULTRA_format">load_data_in_ULTRA_format() (ultra.utils.data_utils.Raw_data method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.BasicPropensityEstimator.loadEstimatorFromFile">loadEstimatorFromFile() (ultra.utils.propensity_estimator.BasicPropensityEstimator method)</a>

      <ul>
        <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.OraclePropensityEstimator.loadEstimatorFromFile">(ultra.utils.propensity_estimator.OraclePropensityEstimator method)</a>
</li>
        <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.RandomizedPropensityEstimator.loadEstimatorFromFile">(ultra.utils.propensity_estimator.RandomizedPropensityEstimator method)</a>
</li>
      </ul></li>
  </ul></td>
</tr></table>

<h2 id="M">M</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.main">main() (in module ultra.utils.propensity_estimator)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.make_ranking_metric_fn">make_ranking_metric_fn() (in module ultra.utils.metrics)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.RankingMetricKey.MAP">MAP (ultra.utils.metrics.RankingMetricKey attribute)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.RankingMetricKey.MAX_LABEL">MAX_LABEL (ultra.utils.metrics.RankingMetricKey attribute)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.base_input_feed.BaseInputFeed.MAX_SAMPLE_ROUND_NUM">MAX_SAMPLE_ROUND_NUM (ultra.input_layer.base_input_feed.BaseInputFeed attribute)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.metrics.mean_average_precision">mean_average_precision() (in module ultra.utils.metrics)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.mean_reciprocal_rank">mean_reciprocal_rank() (in module ultra.utils.metrics)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.merge_TFSummary">merge_TFSummary() (in module ultra.utils.data_utils)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.BaseRankingModel.model_parameters">model_parameters (ultra.ranking_model.base_ranking_model.BaseRankingModel attribute)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.RankingMetricKey.MRR">MRR (ultra.utils.metrics.RankingMetricKey attribute)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="N">N</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.navie_algorithm.NavieAlgorithm">NavieAlgorithm (class in ultra.learning_algorithm.navie_algorithm)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.RankingMetricKey.NDCG">NDCG (ultra.utils.metrics.RankingMetricKey attribute)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.team_draft_interleave.TeamDraftInterleaving.next_index_to_add">next_index_to_add() (ultra.utils.team_draft_interleave.TeamDraftInterleaving method)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.BaseRankingModel.NORM_FUNC_DIC">NORM_FUNC_DIC (ultra.ranking_model.base_ranking_model.BaseRankingModel attribute)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.NormalizationFunctions">NormalizationFunctions (class in ultra.ranking_model.base_ranking_model)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.normalized_discounted_cumulative_gain">normalized_discounted_cumulative_gain() (in module ultra.utils.metrics)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="O">O</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.OraclePropensityEstimator">OraclePropensityEstimator (class in ultra.utils.propensity_estimator)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.RankingMetricKey.ORDERED_PAIR_ACCURACY">ORDERED_PAIR_ACCURACY (ultra.utils.metrics.RankingMetricKey attribute)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.ordered_pair_accuracy">ordered_pair_accuracy() (in module ultra.utils.metrics)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.output_ranklist">output_ranklist() (in module ultra.utils.data_utils)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.BasicPropensityEstimator.outputEstimatorToFile">outputEstimatorToFile() (ultra.utils.propensity_estimator.BasicPropensityEstimator method)</a>

      <ul>
        <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.OraclePropensityEstimator.outputEstimatorToFile">(ultra.utils.propensity_estimator.OraclePropensityEstimator method)</a>
</li>
        <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.RandomizedPropensityEstimator.outputEstimatorToFile">(ultra.utils.propensity_estimator.RandomizedPropensityEstimator method)</a>
</li>
      </ul></li>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.override_from_dict">override_from_dict() (ultra.utils.hparams.HParams method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="P">P</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.Raw_data.pad">pad() (ultra.utils.data_utils.Raw_data method)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.base_algorithm.BaseAlgorithm.PADDING_SCORE">PADDING_SCORE (ultra.learning_algorithm.base_algorithm.BaseAlgorithm attribute)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.pairwise_debias.PairDebias">PairDebias (class in ultra.learning_algorithm.pairwise_debias)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.base_algorithm.BaseAlgorithm.pairwise_cross_entropy_loss">pairwise_cross_entropy_loss() (ultra.learning_algorithm.base_algorithm.BaseAlgorithm method)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.navie_algorithm.NavieAlgorithm.pairwise_loss">pairwise_loss() (ultra.learning_algorithm.navie_algorithm.NavieAlgorithm method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.parse">parse() (ultra.utils.hparams.HParams method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.parse_json">parse_json() (ultra.utils.hparams.HParams method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.parse_TFSummary_from_bytes">parse_TFSummary_from_bytes() (in module ultra.utils.data_utils)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.hparams.parse_values">parse_values() (in module ultra.utils.hparams)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.pdgd.PDGD">PDGD (class in ultra.learning_algorithm.pdgd)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.RankingMetricKey.PRECISION">PRECISION (ultra.utils.metrics.RankingMetricKey attribute)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.precision">precision() (in module ultra.utils.metrics)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.click_simulation_feed.ClickSimulationFeed.prepare_sim_clicks_with_index">prepare_sim_clicks_with_index() (ultra.input_layer.click_simulation_feed.ClickSimulationFeed method)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed.prepare_true_labels_with_index">prepare_true_labels_with_index() (ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed method)</a>

      <ul>
        <li><a href="ultra.input_layer.html#ultra.input_layer.direct_label_feed.DirectLabelFeed.prepare_true_labels_with_index">(ultra.input_layer.direct_label_feed.DirectLabelFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed.prepare_true_labels_with_index">(ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed.prepare_true_labels_with_index">(ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed method)</a>
</li>
      </ul></li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.base_input_feed.BaseInputFeed.preprocess_data">preprocess_data() (ultra.input_layer.base_input_feed.BaseInputFeed static method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="R">R</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.propensity_estimator.RandomizedPropensityEstimator">RandomizedPropensityEstimator (class in ultra.utils.propensity_estimator)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.base_algorithm.BaseAlgorithm.ranking_model">ranking_model() (ultra.learning_algorithm.base_algorithm.BaseAlgorithm method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.metrics.RankingMetricKey">RankingMetricKey (class in ultra.utils.metrics)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.Raw_data">Raw_data (class in ultra.utils.data_utils)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.read_data">read_data() (in module ultra.utils.data_utils)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.regression_EM.RegressionEM">RegressionEM (class in ultra.learning_algorithm.regression_EM)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.ActivationFunctions.RELU">RELU (ultra.ranking_model.base_ranking_model.ActivationFunctions attribute)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.data_utils.Raw_data.remove_invalid_data">remove_invalid_data() (ultra.utils.data_utils.Raw_data method)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.base_algorithm.BaseAlgorithm.remove_padding_for_metric_eval">remove_padding_for_metric_eval() (ultra.learning_algorithm.base_algorithm.BaseAlgorithm method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="S">S</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.ActivationFunctions.SELU">SELU (ultra.ranking_model.base_ranking_model.ActivationFunctions attribute)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.ipw_rank.selu">selu() (in module ultra.learning_algorithm.ipw_rank)</a>

      <ul>
        <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.selu">(in module ultra.ranking_model.base_ranking_model)</a>
</li>
      </ul></li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.DLA.separate_gradient_update">separate_gradient_update() (ultra.learning_algorithm.dla.DLA method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.set_from_map">set_from_map() (ultra.utils.hparams.HParams method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.set_hparam">set_hparam() (ultra.utils.hparams.HParams method)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.set_model_structure">set_model_structure() (ultra.utils.hparams.HParams method)</a>
</li>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.ActivationFunctions.SIGMOID">SIGMOID (ultra.ranking_model.base_ranking_model.ActivationFunctions attribute)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.ipw_rank.IPWrank.sigmoid_loss">sigmoid_loss() (ultra.learning_algorithm.ipw_rank.IPWrank method)</a>

      <ul>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.navie_algorithm.NavieAlgorithm.sigmoid_loss">(ultra.learning_algorithm.navie_algorithm.NavieAlgorithm method)</a>
</li>
      </ul></li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.sigmoid_prob">sigmoid_prob() (in module ultra.learning_algorithm.dla)</a>
</li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed.simulate_clicks_online">simulate_clicks_online() (ultra.input_layer.deterministic_online_simulation_feed.DeterministicOnlineSimulationFeed method)</a>

      <ul>
        <li><a href="ultra.input_layer.html#ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed.simulate_clicks_online">(ultra.input_layer.interleaving_deterministic_online_simulation_feed.InterleavingDeterministicOnlineSimulationFeed method)</a>
</li>
        <li><a href="ultra.input_layer.html#ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed.simulate_clicks_online">(ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.DLA.softmax_loss">softmax_loss() (ultra.learning_algorithm.dla.DLA method)</a>

      <ul>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.ipw_rank.IPWrank.softmax_loss">(ultra.learning_algorithm.ipw_rank.IPWrank method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.navie_algorithm.NavieAlgorithm.softmax_loss">(ultra.learning_algorithm.navie_algorithm.NavieAlgorithm method)</a>
</li>
      </ul></li>
      <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.base_algorithm.BaseAlgorithm.step">step() (ultra.learning_algorithm.base_algorithm.BaseAlgorithm method)</a>

      <ul>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dbgd.DBGD.step">(ultra.learning_algorithm.dbgd.DBGD method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.dla.DLA.step">(ultra.learning_algorithm.dla.DLA method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.ipw_rank.IPWrank.step">(ultra.learning_algorithm.ipw_rank.IPWrank method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.navie_algorithm.NavieAlgorithm.step">(ultra.learning_algorithm.navie_algorithm.NavieAlgorithm method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.pairwise_debias.PairDebias.step">(ultra.learning_algorithm.pairwise_debias.PairDebias method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.pdgd.PDGD.step">(ultra.learning_algorithm.pdgd.PDGD method)</a>
</li>
        <li><a href="ultra.learning_algorithm.html#ultra.learning_algorithm.regression_EM.RegressionEM.step">(ultra.learning_algorithm.regression_EM.RegressionEM method)</a>
</li>
      </ul></li>
      <li><a href="ultra.input_layer.html#ultra.input_layer.stochastic_online_simulation_feed.StochasticOnlineSimulationFeed">StochasticOnlineSimulationFeed (class in ultra.input_layer.stochastic_online_simulation_feed)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="T">T</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.ranking_model.html#ultra.ranking_model.base_ranking_model.ActivationFunctions.TANH">TANH (ultra.ranking_model.base_ranking_model.ActivationFunctions attribute)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.team_draft_interleave.TeamDraftInterleaving">TeamDraftInterleaving (class in ultra.utils.team_draft_interleave)</a>
</li>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.to_json">to_json() (ultra.utils.hparams.HParams method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="U">U</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.html#module-ultra">ultra (module)</a>
</li>
      <li><a href="ultra.input_layer.html#module-ultra.input_layer">ultra.input_layer (module)</a>
</li>
      <li><a href="ultra.input_layer.html#module-ultra.input_layer.base_input_feed">ultra.input_layer.base_input_feed (module)</a>
</li>
      <li><a href="ultra.input_layer.html#module-ultra.input_layer.click_simulation_feed">ultra.input_layer.click_simulation_feed (module)</a>
</li>
      <li><a href="ultra.input_layer.html#module-ultra.input_layer.deterministic_online_simulation_feed">ultra.input_layer.deterministic_online_simulation_feed (module)</a>
</li>
      <li><a href="ultra.input_layer.html#module-ultra.input_layer.direct_label_feed">ultra.input_layer.direct_label_feed (module)</a>
</li>
      <li><a href="ultra.input_layer.html#module-ultra.input_layer.interleaving_deterministic_online_simulation_feed">ultra.input_layer.interleaving_deterministic_online_simulation_feed (module)</a>
</li>
      <li><a href="ultra.input_layer.html#module-ultra.input_layer.stochastic_online_simulation_feed">ultra.input_layer.stochastic_online_simulation_feed (module)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#module-ultra.learning_algorithm">ultra.learning_algorithm (module)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#module-ultra.learning_algorithm.base_algorithm">ultra.learning_algorithm.base_algorithm (module)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#module-ultra.learning_algorithm.dbgd">ultra.learning_algorithm.dbgd (module)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#module-ultra.learning_algorithm.dla">ultra.learning_algorithm.dla (module)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#module-ultra.learning_algorithm.ipw_rank">ultra.learning_algorithm.ipw_rank (module)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.learning_algorithm.html#module-ultra.learning_algorithm.navie_algorithm">ultra.learning_algorithm.navie_algorithm (module)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#module-ultra.learning_algorithm.pairwise_debias">ultra.learning_algorithm.pairwise_debias (module)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#module-ultra.learning_algorithm.pdgd">ultra.learning_algorithm.pdgd (module)</a>
</li>
      <li><a href="ultra.learning_algorithm.html#module-ultra.learning_algorithm.regression_EM">ultra.learning_algorithm.regression_EM (module)</a>
</li>
      <li><a href="ultra.ranking_model.html#module-ultra.ranking_model">ultra.ranking_model (module)</a>
</li>
      <li><a href="ultra.ranking_model.html#module-ultra.ranking_model.base_ranking_model">ultra.ranking_model.base_ranking_model (module)</a>
</li>
      <li><a href="ultra.ranking_model.html#module-ultra.ranking_model.linear">ultra.ranking_model.linear (module)</a>
</li>
      <li><a href="ultra.utils.html#module-ultra.utils">ultra.utils (module)</a>
</li>
      <li><a href="ultra.utils.html#module-ultra.utils.data_utils">ultra.utils.data_utils (module)</a>
</li>
      <li><a href="ultra.utils.html#module-ultra.utils.hparams">ultra.utils.hparams (module)</a>
</li>
      <li><a href="ultra.utils.html#module-ultra.utils.metrics">ultra.utils.metrics (module)</a>
</li>
      <li><a href="ultra.utils.html#module-ultra.utils.propensity_estimator">ultra.utils.propensity_estimator (module)</a>
</li>
      <li><a href="ultra.utils.html#module-ultra.utils.sys_tools">ultra.utils.sys_tools (module)</a>
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      <li><a href="ultra.utils.html#module-ultra.utils.team_draft_interleave">ultra.utils.team_draft_interleave (module)</a>
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<h2 id="V">V</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="ultra.utils.html#ultra.utils.hparams.HParams.values">values() (ultra.utils.hparams.HParams method)</a>
</li>
  </ul></td>
</tr></table>



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